A Data-Driven Method to Identify (Correlated) Changes in Chronological Corpora. Issue 4 (2nd October 2017) - Koplenig, Alexander
Abstract: In this paper, an exploratory data-driven method is presented that extracts word-types from diachronic corpora that have undergone the most pronounced change in frequency of occurrence in a given period of time. Combined with statistical methods from time series analysis, the method is able to find meaningful patterns and relationships in diachronic corpora, an idea that is still uncommon in linguistics. This indicates that the approach can facilitate an improved understanding of diachronic processes.